A Data Standards Weblog

Friday, 24 August 2012

Big Data for Healthcare

The Institute of Medicine is calling for a
“Knowledge Network of Disease”. By bringing together diverse data on health,
new discoveries can be made. Healthcare can get smarter, faster, and more
evenly distributed.

Reporting on developments in The Atlantic,
David A. Shaywitz highlights the tension facing all data aggregators: whether
it's possible to create a single, coherent and correct data model, or whether
it's better to use a more ad hoc approach. He quotes system biologist Eric
Schadt: “The grand data model of everything in biology has been tried over and
over again and ultimately it comes crashing down because once you lock in a
model, you constrain the types of questions you can ask of the data. The
information half life is short, and we know and understand so little about what
the data can actually tell us that we don't really understand the questions
that ultimately will be the most useful.”

How do we build a knowledge structure when
we don't know what we want to know? It's a problem we face in business too. However, the problem can be attacked in an
incremental way. There are levels of detail at which healthcare professionals
will agree. They'll agree that there's such a thing as a patient, for example.
They are also likely to agree on the major biological systems and organs. They
will also probably agree on a core set of signs and symptoms.

There will be a point at which interested
parties can no longer agree on definitions of items or relationships. But that
doesn't mean the modeling approach should be abandoned. We have to tolerate
fuzziness and ambiguity at the depths and fringes of our knowledge structures.
That's how we learn.

As healthcare data sets become larger,
researchers will use analytics to discover new types and constellations of
facts. These discoveries will sharpen the resolution of the outlying fuzzy
areas. So the model will become more detailed and more effective in response to
its use in the field.

The idea that standards need to be
all-or-nothing is one of the myths of information management. Standards exist
to facilitate action, not constrain it.
You don't have to have a grand data model. But you need a model. Instead of thinking that a model or
standard “locks in” users, we need to manage standards as evolving tools that
learn from users as well as supporting them. Standards must lock step with the
communities they serve. Database for Medical Knowledge

ACORD LOMA DAILY NEWS

New Book

My latest book presents the challenges members face when adopting industry standards as well as the opportunities that come as a result. It features my discussions with many people over many years and follows the foundation I set in my first book "The Business Information Revolution".

Industry standards are never adopted in a vacuum. They become part and parcel of all the trials and tribulations managers face in their day to day work. ACORD Standards are always part of a larger software development project that brings along people, priorities and politics. Adopting industry standards isn't simple, but the benefits far outweigh the problems of building and maintaining proprietary alternatives.

I trust that you will appreciate my frankness, identify with some of the challenges and learn from what others have done to pave the way.

Previous Book

This is a PDF version of my book. You have my permission to view, save and print copies for your personal use. Use your browser "Back" button to return to the blog after you visit or print a chapter. If you want a clean copy, it's available at the Amazon bookstore.